Daily mapping of Australian Plague Locust abundance
1.
Stige, L. C., Chan, K.-S., Zhang, Z., Frank, D. & Stenseth, N. C. Thousand-year-long Chinese time series reveals climatic forcing of decadal locust dynamics. Proc. Natl. Acad. Sci. 104, 16188–16193 (2007).
ADS CAS PubMed Article Google Scholar
2.
Walker, F. Catalogue of the Specimens of Dermaptera Saltatoria in Collection of the British Museum. Part III. 485–594 (British Museum (Natural History), 1870).
3.
Wright, D. E. Analysis of the development of major plagues of the Australian plague locust Chortoicetes terminifera (Walker) using a simulation model. Aust. J. Ecol. 12, 423–437 (1987).
Article Google Scholar
4.
Deveson, E. D. & Walker, P. W. Not a one-way trip: Historical distribution data for Australian plague locusts support frequent seasonal exchange migrations. J. Orthoptera Res. 14, 91–105 (2005).
Article Google Scholar
5.
Wang, H. Quantitative assessment of Australian plague locust habitats in the inland of eastern Australia using RS and GIS technologies in Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI vol. 9239 92390D (International Society for Optics and Photonics, 2014).
6.
Chapuis, M.-P. et al. Challenges to assessing connectivity between massive populations of the Australian plague locust. Proc. R. Soc. B Biol. Sci. 278, 3152–3160 (2011).
Article Google Scholar
7.
Murray, D. A. H., Clarke, M. B. & Ronning, D. A. Estimating invertebrate pest losses in six major Australian grain crops. Aust. J. Entomol. 52, 227–241 (2013).
Article Google Scholar
8.
Zhang, L., Lecoq, M., Latchininsky, A. & Hunter, D. Locust and grasshopper management. Annu. Rev. Entomol. 64, 15–34 (2019).
CAS PubMed Article Google Scholar
9.
Adriaansen, C., Woodman, J., Deveson, E. & Drake, V. The Australian Plague Locust: risk and response. Environ. Hazards Risks Disasters Biol https://doi.org/10.1016/B978-0-12-394847-2.00005-X (2016).
Article Google Scholar
10.
Farrow, R. A. & Longstaff, B. C. Comparison of the annual rates of increase of locusts in relation to the incidence of plagues. Oikos 2, 207–222 (1986).
Article Google Scholar
11.
Wardhaugh, K. G. The effects of temperature and moisture on the inception of diapause in eggs of the Australian plague locust, Chortoicetes terminifera Walker (Orthoptera: Acrididae). Aust. J. Ecol. 5, 187–191 (1980).
Article Google Scholar
12.
Wardhaugh, K. G. Diapause strategies in the Australian plague locust (Chortoicetes terminifera Walker). In The evolution of insect life cycles 89–104 (Springer, Berlin, 1986).
Google Scholar
13.
Clark, D. P. Flights after sunset by the Australian plague locust, Chortoicetes terminifera (Walker) and their significance in dispersal and migration. Aust. J. Zool. 19, 159–176 (1971).
Article Google Scholar
14.
Farrow, R. A. Origin and decline of the 1973 plague locust outbreak in central western New South Wales. Aust. J. Zool. 25, 455–489 (1977).
Article Google Scholar
15.
Wang, B. et al. Future climate change likely to reduce the Australian plague locust (Chortoicetes terminifera) seasonal outbreaks. Sci. Total Environ. 668, 947–957 (2019).
ADS CAS PubMed Article Google Scholar
16.
Veran, S. et al. Modeling spatiotemporal dynamics of outbreaking species: influence of environment and migration in a locust. Ecology 96, 737–748 (2015).
PubMed Article Google Scholar
17.
Maywald, G., Kriticos, D., Sutherst, R. & Bottomley, W. DYMEX model builder version 3: user’s guide. (2007).
18.
Meynard, C. N. et al. Climate-driven geographic distribution of the desert locust during recession periods: Subspecies’ niche differentiation and relative risks under scenarios of climate change. Glob. Change Biol. 23, 4739–4749 (2017).
ADS Article Google Scholar
19.
Piou, C. et al. Coupling historical prospection data and a remotely-sensed vegetation index for the preventative control of Desert locusts. Basic Appl. Ecol. 14, 593–604 (2013).
Article Google Scholar
20.
Tratalos, J. A., Cheke, R. A., Healey, R. G. & Stenseth, N. C. Desert locust populations, rainfall and climate change: Insights from phenomenological models using gridded monthly data. Clim. Res. 43, 229–239 (2010).
Article Google Scholar
21.
Tian, H. et al. Reconstruction of a 1,910-y-long locust series reveals consistent associations with climate fluctuations in China. Proc. Natl. Acad. Sci. 108, 14521–14526 (2011).
ADS CAS PubMed Article Google Scholar
22.
Ehrlén, J. & Morris, W. F. Predicting changes in the distribution and abundance of species under environmental change. Ecol. Lett. 18, 303–314 (2015).
PubMed PubMed Central Article Google Scholar
23.
Croft, S., Chauvenet, A. L. & Smith, G. C. A systematic approach to estimate the distribution and total abundance of British mammals. PLoS ONE 12, e0176339 (2017).
PubMed PubMed Central Article CAS Google Scholar
24.
Woodman, J. D. High-temperature survival is limited by food availability in first-instar locust nymphs. Aust. J. Zool. 58, 323–330 (2011).
Article Google Scholar
25.
Guisan, A., Edwards, T. C. & Hastie, T. Generalized linear and generalized additive models in studies of species distributions: Setting the scene. Ecol. Model. 157, 89–100 (2002).
Article Google Scholar
26.
Yee, T. W. & Mitchell, N. D. Generalized additive models in plant ecology. J. Veg. Sci. 2, 587–602 (1991).
Article Google Scholar
27.
Bučas, M. et al. Empirical modelling of benthic species distribution, abundance, and diversity in the Baltic Sea: Evaluating the scope for predictive mapping using different modelling approaches. ICES J. Mar. Sci. 70, 1233–1243 (2013).
Article Google Scholar
28.
Heersink, D. K. et al. Statistical modeling of a larval mosquito population distribution and abundance in residential Brisbane. J. Pest Sci. 89, 267–279 (2016).
Article Google Scholar
29.
Jeffrey, S. J., Carter, J. O., Moodie, K. B. & Beswick, A. R. Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environ. Model. Softw. 16, 309–330 (2001).
Article Google Scholar
30.
Tozer, C. R., Kiem, A. S. & Verdon-Kidd, D. C. On the uncertainties associated with using gridded rainfall data as a proxy for observed. Hydrol. Earth Syst. Sci. 16, 1481–1499 (2012).
ADS Article Google Scholar
31.
Gregg, P. Development of the Australian Plague Locust, Chortoicetes terminifera, in relation to weather I. Effects of constant temperature and humidity. Aust. J. Entomol. 22, 247–251 (1983).
Article Google Scholar
32.
Pruess, K. P. Day-degree methods for pest management. Environ. Entomol. 12, 613–619 (1983).
Article Google Scholar
33.
McVicar, T. R., Briggs, P. R., King, E. A. & Raupach, M. R. A review of predictive modelling from a natural resource management perspective: the role of remote sensing of the terrestrial environment (CSIRO Land and Water CSIRO Earth Observation Centre, Canberra, 2003).
Google Scholar
34.
Grundy, M. J. et al. Soil and landscape grid of Australia. Soil Res. 53, 835–844 (2015).
Article Google Scholar
35.
Cressie, N. & Wikle, C. K. Statistics for spatio-temporal data (John Wiley & Sons, New York, 2015).
Google Scholar
36.
James, G., Witten, D., Hastie, T. & Tibshirani, R. An introduction to statistical learning (Springer, Berlin, 2013).
Google Scholar
37.
Nelder, J. A. & Wedderburn, R. W. Generalized linear models. J. R. Stat. Soc. Ser. Gen. 135, 370–384 (1972).
Article Google Scholar
38.
Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).
PubMed PubMed Central Article Google Scholar
39.
Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer-Verlag, Berlin, 2002). https://doi.org/10.1007/978-0-387-21706-2.
Google Scholar
40.
Wood, S. N., Goude, Y. & Shaw, S. Generalized additive models for large data sets. J. R. Stat. Soc. Ser. C Appl. Stat. 64, 139–155 (2015).
MathSciNet Article Google Scholar
41.
Clark, D. P. The influence of rainfall on the densities of adult Chortoicetes terminifera (Walker) in central western New South Wales, 1965–73. Aust. J. Zool. 22, 365–386 (1974).
Article Google Scholar
42.
Shelford, V. E. The ecology of North America. Ecol. N. Am. 2, 2 (1963).
Google Scholar
43.
Deveson, E. D. Satellite normalized difference vegetation index data used in managing Australian plague locusts. J. Appl. Remote Sens. 7, 075096 (2013).
ADS Article Google Scholar
44.
Kuhnert, P. M. & Lucchesi, L. Vizumap: An R package for visualizing uncertainty in spatial data (Zenodo, Boca Raton, 2018). https://doi.org/10.5281/zenodo.1479951.
Google Scholar
45.
Lucchesi, L. R. & Wikle, C. K. Visualizing uncertainty in areal data with bivariate choropleth maps, map pixelation and glyph rotation. Stat 6, 292–302 (2017).
MathSciNet Article Google Scholar
46.
Benfekih, L., Chara, B. & Doumandji-Mitiche, B. Influence of anthropogenic impact on the habitats and swarming risks of Dociostaurus maroccanus and Locusta migratoria (Orthoptera, Acrididae) in the Algerian Sahara and the semi-arid zone. J. Orthoptera Res. 11, 243–250 (2002).
Article Google Scholar
47.
Štrumbelj, E. & Kononenko, I. Explaining prediction models and individual predictions with feature contributions. Knowl. Inf. Syst. 41, 647–665 (2014).
Article Google Scholar
48.
Escorihuela, M. J. et al. SMOS based high resolution soil moisture estimates for desert locust preventive management. Remote Sens. Appl. Soc. Environ. 11, 140–150 (2018).
Google Scholar
49.
Myneni, R. B. & Williams, D. L. On the relationship between FAPAR and NDVI. Remote Sens. Environ. 49, 200–211 (1994).
ADS Article Google Scholar
50.
Hu, G. et al. Long-term seasonal forecasting of a major migrant insect pest: the brown planthopper in the Lower Yangtze River Valley. J. Pest Sci. 92, 417–428 (2019).
Article Google Scholar More